2 private links
Marker converts PDF to markdown quickly and accurately. Supports a wide range of documents (optimized for books and scientific papers) [...] Here are some known limitations that are on the roadmap to address: Marker will not convert 100% of equations to LaTeX. [...] marker /path/to/input/folder /path/to/output/folder --workers 10 --max 10 --metadata_file /path/to/metadata.json --min_length 10000 --workers is the number of pdfs to convert at once. [...] Then run benchmark.py like this: python benchmark.py data/pdfs data/references report.json --nougat This will benchmark marker against other text extraction methods.
https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/ https://GitHub.com/microsoft/AI-For-Beginners/issues/ https://GitHub.com/microsoft/AI-For-Beginners/pulls/ http://makeapullrequest.com https://GitHub.com/microsoft/AI-For-Beginners/watchers/ https://GitHub.com/microsoft/AI-For-Beginners/network/ https://GitHub.com/microsoft/AI-For-Beginners/stargazers/ https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/sketchnotes/ai-overview.png In this curriculum, you will learn: Different approaches to Artificial Intelligence, including the "good old" symbolic approach with Knowledge Representation and reasoning (https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence). [...] We will illustrate the concepts behind these important topics using code in two of the most popular frameworks - http://Tensorflow.org and http://pytorch.org. [...] For a gentle introduction to AI in the Cloud topics you may consider taking the https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste Learning Path. [...] Fork this repo, https://docsify.js.org/#/quickstart on your local machine, and then in the etc/docsify folder of this repo, type docsify serve.
https://xingangpan.github.io/ · https://ayushtewari.com/ · https://people.mpi-inf.mpg.de/~tleimkue/ · https://lingjie0206.github.io/ · https://www.meka.page/ · http://www.mpi-inf.mpg.de/~theobalt/ SIGGRAPH 2023 Conference Proceedings https://github.com/XingangPan/DragGAN/blob/main/DragGAN.gif https://pytorch.org/get-started/locally/ https://twitter.com/XingangP https://arxiv.org/abs/2305.10973 https://vcai.mpi-inf.mpg.de/projects/DragGAN/ https://colab.research.google.com/drive/1mey-IXPwQC_qSthI5hO-LTX7QL4ivtPh?usp=sharing [...] To start the DragGAN GUI, simply run: If you are using windows, you can run: This GUI supports editing GAN-generated images. [...] You can run DragGAN Gradio demo as well, this is universal for both windows and linux: python visualizer_drag_gradio.py [...] Any form of use and derivative of this code must preserve the watermarking functionality showing "AI Generated".
Unified Model Serving Framework
🏹 Scalable with powerful performance optimizations
abstraction scales model inference separately from your custom code and multi-core CPU utilization with automatic provisioning [...]
We strip out as much potentially sensitive information as possible, and we will never collect user code, model data, model names, or stack traces.